Abstract
The study considers robust estimation of linear regression parameters by the regularization method, the pseudoinverse method, and the Bayesian method allowing for correlations and errors in the data. Regularizing algorithms are constructed and their relationship with pseudoinversion, the Bayesian approach, and BLUE is investigated.
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